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skill-cortex

Skill Cortex is the system's capability cortex. When lacking ability, it autonomously acquires Skills from ClawHub or GitHub, then releases them after use. Every invocation is learned and reinforced by the cortex — future identical tasks fire as reflexes, bypassing search. Manages only short-term capability memory; never interferes with long-term Skills. Continuously restructures its own capability architecture through reinforcement and decay, achieving ongoing evolution.

ankwu0010 来源安装数☆ 0 仓库 Stars

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

SkillHub CLI

skillhub install ankwu001/skill-cortex-pub

打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Skill Cortex

Triggers when installed Skills cannot complete the current task. If you can handle it yourself, just do it — do not trigger this flow.

Cortex data file: ~/.openclaw/skill-cortex/cortex.json (schema in DESIGN.md).

Phase 1: Perception

  1. Read cortex.json (if missing or corrupt, skip to step 3).
  2. Semantically match the users task description against sensory.patterns signals.
  3. On miss, search ClawHub.

Phase 2: Validation

Present candidates to the user with safety info. Wait for explicit approval before installing.

Phase 3: Execution

Install the Skill, generate an execution plan, execute the task. On failure, auto-recover or switch to next candidate.

Phase 4: Learning

Update the cortex memory. Successful Skills gain weight; failed ones decay.

Boundary Rules

  1. Never interfere with long-term Skills.
  2. Installation requires user confirmation.
  3. System dependency installation requires separate confirmation.
  4. Write operations never enter reflex.
  5. Max 2 candidate switches.

来源信息

Source
github
Repository
openclaw/skills
Path
skills/ankwu001/skill-cortex-pub
Version
—
Commit
db69fe9eaf043c9995025d22c4307d77d1ee0cb0
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。

README

Skill Cortex

A self-evolving capability manager for OpenClaw agents.

Skill Cortex gives your agent the ability to autonomously find, install, use, and discard Skills from ClawHub — and learn from every interaction. The more you use it, the faster it gets.

The Problem

OpenClaw loads every installed Skill into the system prompt. More Skills = more tokens burned per conversation, even when most are irrelevant to the current task. But uninstalling them means losing capability.

The Solution

Skill Cortex introduces a cached Skill layer — a dynamic, temporary workspace that sits on top of your permanent Skills:

┌─────────────────────────────────────────────┐
│  User Task                                  │
├─────────────────────────────────────────────┤
│  Skill Cortex (this Skill)                  │
│  ┌────────────────────────────────────────┐ │
│  │ Sensory   → recognize task type        │ │
│  │ Motor     → route to best Skill        │ │
│  │ Prefrontal→ apply past experience      │ │
│  └────────────────────────────────────────┘ │
├─────────────────────────────────────────────┤
│  Cached Skills  (on-demand, auto-cleanup)   │
├─────────────────────────────────────────────┤
│  Long-term Skills  (user-installed, native) │
└─────────────────────────────────────────────┘

How It Works

Phase 1 — Perception: Check local memory first. If the cortex has seen this type of task before, it routes directly to the best known Skill. Otherwise, search ClawHub.

Phase 2 — Validation: Present candidates to the user with safety info (stars, downloads, VirusTotal scan, source). Nothing installs without explicit approval.

Phase 3 — Execution: Install the Skill, generate an execution plan with side-effect warnings, execute the task. On failure, auto-recover or switch to the next candidate (max 2 switches).

Phase 4 — Learning: Update the cortex memory. Successful Skills gain weight; fail...

来源内容

SKILL.md
# Skill Cortex

Triggers when installed Skills cannot complete the current task. If you can handle it yourself, just do it — do not trigger this flow.

Cortex data file: ~/.openclaw/skill-cortex/cortex.json (schema in DESIGN.md).

## Phase 1: Perception

1. Read cortex.json (if missing or corrupt, skip to step 3).
2. Semantically match the users task description against sensory.patterns signals.
3. On miss, search ClawHub.

## Phase 2: Validation

Present candidates to the user with safety info. Wait for explicit approval before installing.

## Phase 3: Execution

Install the Skill, generate an execution plan, execute the task. On failure, auto-recover or switch to next candidate.

## Phase 4: Learning

Update the cortex memory. Successful Skills gain weight; failed ones decay.

## Boundary Rules

1. Never interfere with long-term Skills.
2. Installation requires user confirmation.
3. System dependency installation requires separate confirmation.
4. Write operations never enter reflex.
5. Max 2 candidate switches.
README
# Skill Cortex

**A self-evolving capability manager for [OpenClaw](https://github.com/openclaw) agents.**

Skill Cortex gives your agent the ability to autonomously find, install, use, and discard Skills from [ClawHub](https://clawhub.ai) — and learn from every interaction. The more you use it, the faster it gets.

## The Problem

OpenClaw loads every installed Skill into the system prompt. More Skills = more tokens burned per conversation, even when most are irrelevant to the current task. But uninstalling them means losing capability.

## The Solution

Skill Cortex introduces a **cached Skill layer** — a dynamic, temporary workspace that sits on top of your permanent Skills:

```
┌─────────────────────────────────────────────┐
│  User Task                                  │
├─────────────────────────────────────────────┤
│  Skill Cortex (this Skill)                  │
│  ┌────────────────────────────────────────┐ │
│  │ Sensory   → recognize task type        │ │
│  │ Motor     → route to best Skill        │ │
│  │ Prefrontal→ apply past experience      │ │
│  └────────────────────────────────────────┘ │
├─────────────────────────────────────────────┤
│  Cached Skills  (on-demand, auto-cleanup)   │
├─────────────────────────────────────────────┤
│  Long-term Skills  (user-installed, native) │
└─────────────────────────────────────────────┘
```

## How It Works

**Phase 1 — Perception:** Check local memory first. If the cortex has seen this type of task before, it routes directly to the best known Skill. Otherwise, search ClawHub.

**Phase 2 — Validation:** Present candidates to the user with safety info (stars, downloads, VirusTotal scan, source). Nothing installs without explicit approval.

**Phase 3 — Execution:** Install the Skill, generate an execution plan with side-effect warnings, execute the task. On failure, auto-recover or switch to the next candidate (max 2 switches).

**Phase 4 — Learning:** Update the cortex memory. Successful Skills gain weight; fail...

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